Automated Student Review System with Computer Vision and Convolutional Neural Network

• Published in: 2021 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) pp. 493 - 497
• Main Authors: Siam, Sadman Chowdhury, Faisal, Abrar, Mahrab, Niazi, Haque, Akm Bahalul, Suvon, Md. Naimul Islam
• Format: Conference Proceeding
• Language: English
• Published: IEEE 19-02-2021
• Subjects: Computational modeling; Computer vision; computervision; convolutional neural network; Convolutional neural networks; data normalization; deeplearning; Faces; features extraction; Predictive models; Task analysis; Tuning
• DOI: 10.1109/ICCCIS51004.2021.9397164

Detecting Emotion from a face is a prevalent topic, and computer vision researchers are continuously working on perfecting this challenging task. Facial emotion is widely used in applications like Snapchat, Face apps, Cameras, etc., to predict emotions from faces, to detect smiles, and many more. The task is very challenging, as a person's facial features vary from one to another. As convolutional neural networks can detect such complicated features so, the idea of deep learning has been used to tackle this problem. We have tried to predict facial emotion from images and generate reviews from that. Since there are already many works on emotion detection, we focused mainly on its application. Our main aim is to design a system that can generate automated reviews from human emotion. We have labeled different facial expressions with some scores and used that score to predict student review in the classroom.